\subsection*{Abstract}
Web applications suffer from poor reliability. Application providers commonly rely on fast failure detection, which is challenging. In this paper, we present a novel technique for automatically detecting user-visible failures by analyzing Web logs. Our technique applies a first-order Markov model to infer anomalous browsing behavior discovered in Web logs as indicators that users have encountered errors. We implemented our technique in a tool called {DefWAP} (\underline{De}tect \underline{F}ailures in \underline{WE}b \underline{A}pplications). We evaluated our technique using \textsc{DefWAP} applied to the Web site of NASA. The results demonstrate the effectiveness of our technique.

